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Provenance Model for Randomized Controlled Trials

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Book cover Data Provenance and Data Management in eScience

Part of the book series: Studies in Computational Intelligence ((SCI,volume 426))

Abstract

This chapter proposes a provenance model for the clinical research domain, focusing on the planning and conduct of randomized controlled trials, and the subsequent analysis and reporting of results from those trials. We look at the provenance requirements for clinical research and trial management of different stakeholders (researchers, clinicians, participants, IT staff) to identify elements needed at multiple levels and stages of the process. In order to address these challenges, a provenance model is defined by extending the Open Provenance Model with domain-specific additions that tie the representation closer to the expertise of medical users, and with the ultimate aim of creating the first OPM profile for randomized controlled clinical trials. As a starting point, we used the domain information model developed at University of Dusseldorf, which conforms to the ICH Guideline for Good Clinical Practice (GCP) standard, thereby ensuring the wider applicability of our work. The application of the model is demonstrated on several examples and queries based on the integrated trial data being captured as part of the TRANSFoRm EU FP7 project.

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Author information

Authors and Affiliations

  1. Imperial College London, London, SW7 2AZ, UK

    Vasa Curcin & Roxana Danger

  2. University of Dusseldorf, Düsseldorf, Germany

    Wolfgang Kuchinke & Christian Ohmann

  3. King’s College London, London, UK

    Simon Miles & Adel Taweel

Authors
  1. Vasa Curcin
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  2. Roxana Danger
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  3. Wolfgang Kuchinke
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  4. Simon Miles
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  5. Adel Taweel
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  6. Christian Ohmann
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Corresponding author

Correspondence to Vasa Curcin .

Editor information

Editors and Affiliations

  1. , Information and Communications, CSIRO, Hobart, 7001, Tasmania, Australia

    Qing Liu

  2. , School of Computing & Mathematical, Auckland University of Technology, Private Bag 92006, Auckland, 1142, New Zealand

    Quan Bai

  3. , Information and Communications, CSIRO, Hobart, 7001, Tasmania, Australia

    Stephen Giugni

  4. , Information Management and Technology, CSIRO, Acton, 2601, Aust Capital Terr, Australia

    Darrell Williamson

  5. Mathematics Informatics and Statistics, CSIRO, Acton, 2601, Aust Capital Terr, Australia

    John Taylor

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Curcin, V., Danger, R., Kuchinke, W., Miles, S., Taweel, A., Ohmann, C. (2013). Provenance Model for Randomized Controlled Trials. In: Liu, Q., Bai, Q., Giugni, S., Williamson, D., Taylor, J. (eds) Data Provenance and Data Management in eScience. Studies in Computational Intelligence, vol 426. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29931-5_1

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  • DOI: https://doi.org/10.1007/978-3-642-29931-5_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29930-8

  • Online ISBN: 978-3-642-29931-5

  • eBook Packages: EngineeringEngineering (R0)

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